Qianli Liao

Publication Activity (10 Years)

Years Active: 2013-2021
Publications (10 Years): 23

Top Topics

Visual Representation

Supervised Learning

Top Venues

Int. J. Autom. Comput.

Publications

Tomaso A. Poggio, Qianli Liao
Explicit regularization and implicit bias in deep network classifiers trained with the square loss. CoRR (2021)
Arturo Deza, Qianli Liao, Andrzej Banburski, Tomaso A. Poggio
Hierarchically Local Tasks and Deep Convolutional Networks. CoRR (2020)
Andrzej Banburski, Qianli Liao, Brando Miranda, Lorenzo Rosasco, Bob Liang, Jack Hidary, Tomaso A. Poggio
Theory III: Dynamics and Generalization in Deep Networks. CoRR (2019)
Tomaso A. Poggio, Andrzej Banburski, Qianli Liao
Theoretical Issues in Deep Networks: Approximation, Optimization and Generalization. CoRR (2019)
Will Xiao, Honglin Chen, Qianli Liao, Tomaso A. Poggio
Biologically-Plausible Learning Algorithms Can Scale to Large Datasets. ICLR (Poster) (2019)
Chiyuan Zhang, Qianli Liao, Alexander Rakhlin, Brando Miranda, Noah Golowich, Tomaso A. Poggio
Theory of Deep Learning IIb: Optimization Properties of SGD. CoRR (2018)
Will Xiao, Honglin Chen, Qianli Liao, Tomaso A. Poggio
Biologically-plausible learning algorithms can scale to large datasets. CoRR (2018)
Tomaso A. Poggio, Qianli Liao, Brando Miranda, Andrzej Banburski, Xavier Boix, Jack Hidary
Theory IIIb: Generalization in Deep Networks. CoRR (2018)
Qianli Liao, Brando Miranda, Andrzej Banburski, Jack Hidary, Tomaso A. Poggio
A Surprising Linear Relationship Predicts Test Performance in Deep Networks. CoRR (2018)
Tomaso A. Poggio, Kenji Kawaguchi, Qianli Liao, Brando Miranda, Lorenzo Rosasco, Xavier Boix, Jack Hidary, Hrushikesh N. Mhaskar
Theory of Deep Learning III: explaining the non-overfitting puzzle. CoRR (2018)
Tomaso A. Poggio, Qianli Liao
Theory II: Landscape of the Empirical Risk in Deep Learning. CoRR (2017)
Hrushikesh N. Mhaskar, Qianli Liao, Tomaso A. Poggio
When and Why Are Deep Networks Better Than Shallow Ones? AAAI (2017)
Vijay Chandrasekhar, Jie Lin, Qianli Liao, Olivier Morère, Antoine Veillard, Ling-Yu Duan, Tomaso A. Poggio
Compression of Deep Neural Networks for Image Instance Retrieval. DCC (2017)
Tomaso A. Poggio, Hrushikesh N. Mhaskar, Lorenzo Rosasco, Brando Miranda, Qianli Liao
Why and when can deep-but not shallow-networks avoid the curse of dimensionality: A review. Int. J. Autom. Comput. 14 (5) (2017)
Vijay Chandrasekhar, Jie Lin, Qianli Liao, Olivier Morère, Antoine Veillard, Ling-Yu Duan, Tomaso A. Poggio
Compression of Deep Neural Networks for Image Instance Retrieval. CoRR (2017)
Qianli Liao, Tomaso A. Poggio
Bridging the Gaps Between Residual Learning, Recurrent Neural Networks and Visual Cortex. CoRR (2016)
Joel Z. Leibo, Qianli Liao, Winrich Freiwald, Fabio Anselmi, Tomaso A. Poggio
View-tolerant face recognition and Hebbian learning imply mirror-symmetric neural tuning to head orientation. CoRR (2016)
Hrushikesh N. Mhaskar, Qianli Liao, Tomaso A. Poggio
Learning Real and Boolean Functions: When Is Deep Better Than Shallow. CoRR (2016)
Qianli Liao, Joel Z. Leibo, Tomaso A. Poggio
How Important Is Weight Symmetry in Backpropagation? AAAI (2016)
Tomaso A. Poggio, Hrushikesh N. Mhaskar, Lorenzo Rosasco, Brando Miranda, Qianli Liao
Why and When Can Deep - but Not Shallow - Networks Avoid the Curse of Dimensionality: a Review. CoRR (2016)
Qianli Liao, Kenji Kawaguchi, Tomaso A. Poggio
Streaming Normalization: Towards Simpler and More Biologically-plausible Normalizations for Online and Recurrent Learning. CoRR (2016)
Qianli Liao, Joel Z. Leibo, Tomaso A. Poggio
How Important is Weight Symmetry in Backpropagation? CoRR (2015)
Joel Z. Leibo, Qianli Liao, Fabio Anselmi, Tomaso A. Poggio
The Invariance Hypothesis Implies Domain-Specific Regions in Visual Cortex. PLoS Comput. Biol. 11 (10) (2015)
Qianli Liao, Joel Z. Leibo, Tomaso A. Poggio
Unsupervised learning of clutter-resistant visual representations from natural videos. CoRR (2014)
Joel Z. Leibo, Qianli Liao, Tomaso A. Poggio
Subtasks of Unconstrained Face Recognition. VISAPP (2) (2014)
Qianli Liao, Joel Z. Leibo, Tomaso A. Poggio
Learning invariant representations and applications to face verification. NIPS (2013)
Qianli Liao, Joel Z. Leibo, Youssef Mroueh, Tomaso A. Poggio
Can a biologically-plausible hierarchy effectively replace face detection, alignment, and recognition pipelines? CoRR (2013)